When an E.coli outbreak at Chipotle Mexican Grill outlets left 55 customers ill, in 2015, the news stories, shutdowns, and investigations shattered the restaurant chain’s reputation. Sales plummeted, and Chipotle’s share price dropped 42%, to a three-year low, where it has languished ever since.
At the heart of the Denver-based company’s crisis was the ever-present problem faced by companies that depend on multiple suppliers to deliver parts and ingredients: a lack of transparency and accountability across complex supply chains. Unable to monitor its suppliers in real time, Chipotle could neither prevent the contamination nor contain it in a targeted way after it was discovered.
Now, a slew of startups and corporations are exploring a radical solution to this problem: using a blockchain to transfer title and record permissions and activity logs so as to track the flow of goods and services between businesses and across borders.
With blockchain technology, the core system that underpins bitcoin, computers of separately owned entities follow a cryptographic protocol to constantly validate updates to a commonly shared ledger. A fundamental advantage of this distributed system, where no single company has control, is that it resolves problems of disclosure and accountability between individuals and institutions whose interests aren’t necessarily aligned. Mutually important data can be updated in real time, removing the need for laborious, error-prone reconciliation with each other’s internal records. It gives each member of the network far greater and timelier visibility of the total activity.
A leading expert claims that the flower industry could save hundreds of millions of dollars just by ensuring supply chain efficiency in the lead-up to Mother’s Day.
Shipments in the floral industry spike ten-fold in the lead up to Mother’s Day and an estimated $2.6 billion is expected to be spent in 2017 even though it’s estimated that 40 per cent of flowers are never even sold.
David Bairstow, Product VP at location specialists Skyhook, reckons that incorporating the internet of things into the cold supply chain could result in massive savings.
He said: “Supply chain is an industry born out of economies of scale. The same applies to the cost of implementing IoT, as scale increases, return on investment increases. It costs pennies to ship individual flowers; however, using supply chain insights to increase efficiencies and reduce waste, can quickly pay for itself.
“Factoring in that the 40% waste due to unsold flowers amounts to $1.04 billion, it is evident that there is massive scope for improvement. If introducing IoT into the cold supply chain leads to decrease in waste by even 10%, that would result in more than $100 million of savings.”
Companies like KaBloom are constantly optimizing the day-to-day supply chain over time to achieve the most efficient path to the consumer. They see a ten-fold increase in volume on days like Mother’s Day and Valentine’s Day and their supply chain remains largely the same, except for the increased volume on those holidays so if the day-to-day efficiencies are optimized, the likelihood of failures happening on the busiest days can be drastically reduced.
Plex Systems, a developer of cloud ERP for manufacturing, has introduced two new analytic applications designed to provide manufacturers insight into supply chain performance and their workforce.
The new Supply Chain and Human Capital analytic applications build on the library of applications in the IntelliPlex Analytic Application Suite, a broad suite of cloud analytics for manufacturing organizations.
The Plex Manufacturing Cloud is designed to connect people, processes, systems and products in manufacturing enterprises. The goal is not only to streamline and automates operations, but also enable greater access to companywide data. The IntelliPlex suite of analytic applications aims to turn that data into configurable, role-based decision support dashboards–with deep drill-down and drill-across capabilities. The IntelliPlex Analytic Application Suite includes analytics for sales, order management, procurement, production and finance professionals.
IntelliPlex Supply Chain Analytic Application
The new IntelliPlex Supply Chain Analytic application provides a dashboard for managing strategic programs, such as enterprise supplier performance, inventory and materials management and customer success. Metrics include:
On-time delivery and return rates by supplier, part, material, etc.
Production backlog by part group, product time, etc.
Spend by supplier and type, including unapproved spend
Inventory turns and aging based on type, location, etc.
Materials management accuracy, adjustments and trends by type, location, etc.
On-time fill rate, customer lead time, average days to ship, fulfillment by location
In conjunction with the announcement, o9 released an eBook titled, “Who Gets the Cheese?”
Aptly named after one of the greatest business books of all time (Who Moved My Cheese?), this resource details one of o9’s systems for optimally allocating resources across initiatives and brands at consumer goods companies.
Founded by executives, practitioners and technologists that have led supply chain innovations for nearly three decades, the o9 team has been quietly developing a game-changing Augmented Intelligence (AI) platform for transforming Integrated Planning and Supply Chain processes.
The team has deployed the AI platform with select clients, including:
Aditya Birla Group
Ainsworth Pet Foods
Speaking on behalf of o9 Solutions, Co-founder and CEO Chakri Gottemukkala said, “While executives we work with hear the buzz around technologies for data sensing, analytics, high performance computing, artificial intelligence and automation, they are also living the reality of slow and siloed planning and decision making because the enterprise operates primarily on spreadsheets, email and PowerPoint.”
This Tax Day, former Microsoft CEO Steve Ballmer launched a new tool designed to make government spending and revenue more accessible to the average citizen.
The website — USAFacts.org — has been slow and buggy for users on Tuesday, apparently due to the level of traffic. It offers interactive graphics showing data on revenue, spending, demographics and program missions.
For example, the site prominently features an infographic created to break down revenue and spending in 2014. Revenue is broken down by origin; spending is broken down by what “mission” of government it serves, based on the functions laid out in the Constitution.
It’s a big-picture view of where U.S. tax dollars come from, and how they’re spent. But click on a subcategory and you’re taken to a more detailed, granular view of that spending.
Ballmer didn’t create the site because he was an expert on government data. Quite the opposite, according to The New York Times’ Dealbook.
The Times says that Ballmer’s wife was pushing her newly-retired husband to get more involved in philanthropy. Ballmer said — according to his own memory, as he described the conversation to the Times — “But come on, doesn’t the government take care of the poor, the sick, the old?”
Speaking to a full house at the BROWZ Client Summit 2016 Sundance Resort, V.P. of Product Development, Aaron Rudd stated “BROWZ OneView is a significant development in the evolution of supply chain management software that will not only meet our clients needs today, but will meet their supply chain needs as they expand in the future.”
BROWZ OneView is an entirely new interface and user experience for BROWZ clients.
“Our goal was to enhance the way our clients interact with our solutions and their supply chain. From conducting a simple supplier search to in-depth analysis across a global supply chain. BROWZ is empowering our clients with the new OneView platform,” Rudd said.
“The software provides meaningful insight into the entire supply chain using key performance indicators which also provides the flexibility to analyze the performance of individual locations or specified risk level with the click of a button.”
IBM announced in June that it has embarked on a quest to create a million new data scientists. It will be adding about 230 of them during its Datapalooza educational event this week in San Francisco, where prospective data scientists are building their first analytics apps.
Next year, it will take its show on the road to a dozen cities around the world, including Berlin, Prague, and Tokyo.
The prospects who signed up for the three-day Datapalooza convened Nov. 11 at Galvanize, the high-tech collaboration space in the South of Market neighborhood, to attend instructional sessions, listen to data startup entrepreneurs, and use workspaces with access to IBM’s newly launched Data Science Workbench and Bluemix cloud services. Bluemix gives them access to Spark, Hadoop, IBM Analytics, and IBM Streams.
Rob Thomas, vice president of product development, IBM Analytics, said the San Francisco event is a test drive for IBM’s 2016 Datapalooza events. “We’re trying to see what works and what doesn’t before going out on the road.”
Thomas said Datapalooza attendees were building out DNA analysis systems, public sentiment analysis systems, and other big data apps.
Note that this article was submitted and accepted by KDnuggest, the most popular blog site about machine learning and knowledge discovery.
I have been using Lean Six Sigma (LSS) to improve business processes for the past 10+ year and am very satisfied with its benefits. Recently, I’ve been working with a consulting firm and a software vendor to implement a machine learning (ML) model to predict remaining useful life (RUL) of service parts. The result which I feel most frustrated is the low accuracy of the resulting model. As shown below, if people measure the deviation as the absolute difference between the actual part life and the predicted one, the resulting model has 127, 60, and 36 days of average deviation for the selected 3 parts. I could not understand why the deviations are so large with machine learning.
After working with the consultants and data scientists, it appears that they can improve the deviation only by 10%. This puzzles me a lot. I thought machine learning is a great new tool to make forecast simple and quick, but I did not expect it could have such large deviation. To me, such deviation, even after the 10% improvement, still renders the forecast useless to the business owners.
One in four businesses exceed US$1 million in losses, but almost half of survey respondents in Asia Pacific did not insure their losses.
Zurich Insurance has revealed the key Asia Pacific findings of the Business Continuity Institute (BCI) “Supply Chain Resilience Report 2016”. Despite six out of ten organisations experiencing at least one supply chain disruption during the past year, with one in four exceeding US$1 million in losses, the report found that almost half of survey respondents in Asia Pacific did not insure their losses.
Partnering with BCI for the eighth year, the annual report is regarded as one of the most authoritative benchmark reports in this business area. The key findings for Asia Pacific (APAC) this year are:
IT/Telecom outages was named as the number one cause of supply chain disruption
One in four organisations experienced cumulative losses of over US$1 million
46% of organisations do not insure their losses, meaning they bore the full brunt of the cost
Only 30% of disruptions occur with an immediate supplier
48% responded that top management have made commitments to supply chain resilience
Businesses across many industries spend millions of dollars employing advanced analytics to manage and improve their supply chains. Organizations look to analytics to help with sourcing raw materials more efficiently, improving manufacturing productivity, optimizing inventory, minimizing distribution cost, and other related objectives.
But the results can be less than satisfactory. It often takes too long to source the data, build the models, and deliver the analytics-based solutions to the multitude of decision makers in an organization. Sometimes key steps in the process are omitted completely. In other words, the solution for improving the supply chain, i.e. advanced analytics, suffers from the same problems that it aims to solve. Therefore, reducing inefficiencies in the analytics supply chain should be a critical component of any analytics initiative in order to generate better outcomes. Because one of us (Zahir) spent twenty years optimizing supply chains with analytics at transportation companies, the concept was a naturally appealing one for us to take a closer look at.
More broadly speaking, the concept of the analytics supply chain is applicable outside of its namesake business domain. It is agnostic to business and analytic domains. Advanced analytics for marketing offers, credit decisions, pricing decisions, or a multitude of other areas could benefit from the analytics supply chain metaphor.